Networks have become indispensable for conducting all forms of business and personal communications. Networked systems allow one to access needed information rapidly, collaborate with partners, and conduct electronic commerce. The benefits offered by Internet technologies are enormous. While computer networks revolutionize the way one does business, risks are introduced. Unauthorized network usage can lead to network congestion or even system failures. Furthermore, attacks on networks can lead to lost money, time, reputation, and confidential information. Effective network monitoring can mitigate these system problems.
High network availability is critical for many enterprises. Many performance problems are related to capacity issues. Unauthorized network usage can slow down the performance of mission critical applications and monopolize available bandwidth. Some unauthorized applications, like a Trojan Horse, can erase or degrade essential data as well possibly provide access to vital confidential information.
Consequently, one primary danger to avoid is having outside intruders gain control of a host on a network. Once control is achieved, private company files can be downloaded, the controlled host can be used to attack other computers inside the firewall, or the controlled host can scan or attack computers anywhere in the world. Many organizations have pursued protection by the implementation of firewalls and intrusion detection systems (IDS). However, no avoidance measures are fail safe. Therefore, monitoring for the presence of unauthorized applications and unauthorized activity is important.
Firewalls merely limit access between networks. Firewalls are typically designed to filter network traffic based on attributes such as source or destination addresses, port numbers, or transport layer protocols. However, firewalls are susceptible to maliciously crafted traffic designed to bypass the blocking rules established. Additionally, firewalls do not provide control of the activities of hosts that are communicating internally behind the established firewalls.
Almost all commercially available IDS are signature-based detection systems or anomaly-based systems. Signature-based detection systems piece together the packets in a connection to collect a stream of bytes being transmitted. The stream is then analyzed for certain strings of characters in the data commonly referred to as “signatures.” These signatures are particular strings that have been discovered in known exploits. The more signatures that are stored in a database, the longer it takes to do an exhaustive search on each data stream. For larger networks with massive amounts of data transferred, a string comparison approach is unfeasible. Substantial computing resources are needed to analyze all of the communication traffic.
Even if a known exploit signature has been discovered, the signature is not useful until it is has been installed and is available to the network. In addition, signature analysis only protects a system from known attacks. Yet, new attacks are being implemented all the time. Unfortunately, a signature-based detection system would not detect these new attacks and therefore, leaves the network vulnerable.
Another approach to intrusion detection includes detection of unusual deviation from normal data traffic commonly referred to as “anomalies.” Like signature-based detection systems, many current anomaly-based intrusion detection systems only detect known methods of attack. Some of these known anomaly-based attacks include TCP/IP stack fingerprinting, half-open attacks, and port scanning. However, systems relying on known attacks are easy to circumnavigate and leave the system vulnerable. In addition, some abnormal network traffic happens routinely, often non-maliciously, in normal network traffic. For example, an incorrectly entered address could be sent to an unauthorized port and be interpreted as an abnormality. Consequently, known anomaly-based systems tend to generate an undesirable number of false alarms, which creates a tendency for all alarms to be ignored.
Some known intrusion detection systems have tried to detect statistical anomalies. This approach involves measuring a baseline and then triggering an alarm when deviation is detected. For example, if a system typically has no traffic from individual workstations at 2 AM, activity during this time frame would be considered suspicious. However, baseline systems have typically been ineffective because the small amount of malicious activity is masked by the large amounts of highly variable normal activity. On the aggregate, it is extremely difficult to detect the potential attacks.
Other intrusion detection systems compare long term profiled data streams to short term profiled data streams. One such system is described in U.S. Pat. No. 6,321,338 to Porras et al. entitled “Network Surveillance.” The system described in this patent does not necessarily analyze all the network traffic, but instead focuses on narrow data streams. The system filters data packets into various data streams and compares short term profiles to profiles collected over a long period. However, data traffic is typically too varied to meaningfully compare short term profiles to long term profiles. For example, merely because the average (File Transfer Protocol) FTP streams may be 3 megabytes over the long term does not indicate that a 20 megabyte stream is an anomaly. Consequently, these systems generate a significant amount of false alarms or the malicious activity can be masked by not analyzing the proper data streams.
Failure to detect the operation of malicious unauthorized application, such as a Trojan Horse, can cause serious harm to a company. A Trojan Horse is a program in which harmful code is contained inside an apparently harmless program or data in such a way that it can gain control of the computer or otherwise do it designed form of damage. A Trojan Horse or virus that penetrates a firewall can cause tremendous damage and spread internally across a local area network.
However, other unauthorized network usage can also be harmful. Employees may waste time and resources by installing and playing games over the network. An authorized web site may utilize crucial bandwidth by providing materials such as pictures, streaming audio, or movies. Even a chat program can waste time and network assets. Valuable resources can also be monopolized by these types of unauthorized network activities. Many of these services can operate behind the firewall, and consequently, a system administrator is not able to effectively control these usages.
Filtering tables in a local area network (LAN) bridge device may allow a system administrator to block communications between particular hosts with other hosts physically connected to a different local area network segments. Filtering tables inhibit forwarding of frames between particular sets of Medium Access Control protocol (MAC) addresses between local area networks (LANs). However, filtering tables do control activities within a collision domain. Furthermore, filtering tables typically only control communications based upon MAC address and not on the service utilized. However, a system administrator may desire to restrict communications between hosts but still allow certain services.
Consequently, a monitoring system is needed that can detect the operation of unauthorized network services. The system needs to be able to differentiate between legitimate network usage and unauthorized activity. Additionally, the system needs to be able to control unauthorized network usage behind a system's firewall. Furthermore, the detection system must be able to function even with the data traffic of larger networks. As a result, a system is needed to alarm upon detection of the operation of any authorized network service in use on any monitored host computer including services utilized inside a firewall.